Development of integrated wetland change detection approach: In case of Erdos Larus Relictus National Nature Reserve, China.

Wetlands are threatened by the global warming and the human exploitation pressure, and have been shrinking quickly in recent years. Timely and accurate wetland area change detection is the primary task for wetland conservation and restoration. The objective of this study is to develop an integrated change detection approach which integrates the advantages of spectral mixture analysis (SMA) and change vector analysis (CVA) for the change identification of wetland dynamics. In the proposed approach, water, vegetation and soil fractions of wetlands were derived by SMA; then, the detailed change information (including change magnitude and 12 change direction categories) were calculated through CVA. The proposed approach was applied for the wetlands change in Erdos Larus Relictus National Nature Reserve (ELRNNR), China, using time-series Landsat images during 1977-2017. We found that the wetland faced serious degradation, with water fraction changed to soil (5.79 km2), to vegetation (1.35 km2) and to both soil and vegetation (3.53 km2). From 1977 to 2000, a slight degradation occurred in the northeast edge of Bojiang Lake and a marginal degradation in Bojiang and Houjia Lakes inside the ELRNNR, with water fraction changed to soil and vegetation. During 2000-2010, severe degradation occurred in ELRNNR, and from 2010 to 2017, the wetland was more susceptible to the precipitation change and human activities. Analysis of the result indicated that the long-term drought and effects of mismanagement as well as misuse by human beings were the driving factors of wetland degradation. The proposed approach in this study achieves a higher accuracy than the classification approach to detect wetland change, with the ability to obtain more detailed change information.